Skills for organizations, partners, the ecosystem

Original Article ↗ Hacker News Discussion ↗

Anthropic Skills and Overall Direction

  • Many see Anthropic leaning into “open standards” to position itself as the serious, research-focused alternative, in contrast to OpenAI’s more closed, Apple-like platform.
  • Some view Skills as a clever funnel: open, portable format that still drives usage back to Claude and partners.
  • Others argue calling this a “standard” is premature; it’s just a published spec.

What Skills Are (Conceptually)

  • Common interpretation: curated, reusable prompts plus optional code that can be lazily loaded into context when needed.
  • Framed as a way to manage context: avoid huge upfront dumps by loading targeted guidance or tools just-in-time.
  • Several people note this is basically formalizing existing prompt patterns.

Skills vs MCP, Agents, and Tools

  • MCP is seen as heavier: remote, authenticated bridges to external systems, with notable context bloat and UX/security issues.
  • Skills are local, lighter on context, and closer to “saved know-how” or “pre-context” than to protocols.
  • Some predict MCP will fade while the agent loop (tool-calling + while loop + discoverability) persists; others argue both remain complementary (MCP for real-world integrations, Skills for specialization).

Adoption, Churn, and Standards Skepticism

  • Frequent worry that Agents/MCP/Skills/A2A may end up as short-lived Netscape-era curiosities.
  • Complaints about “JavaScript framework energy”: many overlapping specs (skills, prompts, slash-commands, agent files) causing fragmentation and fatigue.
  • Debate over whether AI “standards” should go through bodies like IETF; some see current efforts as marketing-driven and technically immature.

Real-world Usage and Benefits

  • Concrete MCP examples: biotech research pipelines, data access layers, and content migrations where LLMs orchestrate traditional tools.
  • Skills used to encode tribal knowledge, workflows, and analysis patterns for teams; some are experimenting with “meta-skills” that generate new skills from sessions.

Limitations and Open Questions

  • Critics say Skills are an awkward patch over model limitations and don’t fundamentally solve hallucinations or context dilution.
  • Others think they’re “good enough” and the best practical pattern so far.
  • Questions remain around composability, state, evolution with user preferences, and whether this truly reduces lock-in or just repackages prompt engineering.

Tone and Culture

  • Thread mixes genuine enthusiasm, production stories, and heavy sarcasm: jokes about left-pad skills, markdown “persona standards,” and AI as a fashion-driven circus.